Avionics display systems such as head-worn displays (HWD), head-up displays (HUD), and enhanced vision (EV) systems (EVS) may employ commercial off-the-shelf (COTS) display devices to reduce the high cost of custom display devices. However, the use of COTS devices lacking DO-254 design assurance may not provide sufficient integrity to maintain compliance with aviation hazard classifications. The conventional solution is the use of multiple independent monitoring schemes. For example, a HUD utilizing one or more COTS display devices may employ a first monitor to ensure that the display is not stuck, flipped, or otherwise generating a hazardously misleading image. A second monitor may ensure that a sudden “all white all bright” (AWAB) condition (or similar shift in brightness) will not incapacitate the pilot. Still another monitor may be employed to ensure that display graphics generators have not mispositioned or misaligned critical symbology merged to the displayed images. Historically, each of these various monitoring systems have been separately implemented using widely varied and complex methods.
If the HUDs and head-worn devices (HWD) of the future are to handle CAT 3 landing credit and low visibility operations (e.g., either with no decision height or a decision height lower than 100 feet (30 m) and a runway visual range not less than 700 feet (200 m)), size, weight, power, and cost (SWaP-C) considerations may mandate the use of COTS devices as opposed to expensive custom engineered displays. Consequently, similar mechanisms of display path monitoring may be required. EV systems, which employ complex COTS devices, provide additional challenges in camera core monitoring. For example, an EVS may have several independent camera cores, produced by a variety of vendors and each providing different scene content. Each core must be shown not to present a critically misaligned or misleading image, or the combined vision stream uniting the feeds of different camera cores may present a hazardously incoherent image. Conventional solutions, which involve matching dead pixels in the output images to known locations, are having trouble keeping up with the continually improving quality of EV systems.